◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Jing Zhang

57 papers hereh-index 4113.4k citations212 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author4
  • middle author50
  • last author2

Across the 56 of 57 papers where every author was matched, so the position is known.

fields
  • cs.CV43
  • cs.IR3
  • cs.LG3
  • cs.AI2
  • cs.CL2
  • cs.SI1
same name
  • Jing Zhang — 39 papers, h 23
  • Jing Zhang — 35 papers, h 32
  • Jing Zhang — 27 papers, h 21
  • Jing Zhang — 23 papers, h 19
  • Jing Zhang — 21 papers, h 11
  • Jing Zhang — 20 papers, h 9

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20172023
most citedSelf-supervised Learning: Generative or Contrastive

1.1k citations · 2.2k across the 55 of their papers we have counts for

collaborators
Showing 2020Show all

4 papers · 1 filter

cs.IR2020

CODE: Contrastive Pre-training with Adversarial Fine-tuning for Zero-shot Expert Linking

Bo Chen, Jing Zhang, Xiaokang Zhang +6

Expert finding, a popular service provided by many online websites such as Expertise Finder, LinkedIn, and AMiner, is beneficial to seeking candidate qualifications, consultants, a…

cs.AI2020★ 60 cited

Empowering Things with Intelligence: A Survey of the Progress, Challenges, and Opportunities in Artificial Intelligence of Things

Jing Zhang, Dacheng Tao

In the Internet of Things (IoT) era, billions of sensors and devices collect and process data from the environment, transmit them to cloud centers, and receive feedback via the int…

cs.CV2020★ 1 cited

Nighttime Dehazing with a Synthetic Benchmark

Jing Zhang, Yang Cao, Zheng-Jun Zha +1

Increasing the visibility of nighttime hazy images is challenging because of uneven illumination from active artificial light sources and haze absorbing/scattering. The absence of…

cs.LG2020★ 1.1k cited

Self-supervised Learning: Generative or Contrastive

Xiao Liu, Fanjin Zhang, Zhenyu Hou +4

Deep supervised learning has achieved great success in the last decade. However, its deficiencies of dependence on manual labels and vulnerability to attacks have driven people to…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.